Multiparental populations (MPPs) encompass more genetic diversity than traditional experimental crosses, enabling a wide array of experimental designs for deep genetic dissections of complex traits. For mouse models, two related MPPs have emerged: the Collaborative Cross (CC) inbred panel and the Diversity Outbred (DO) population. Additionally, the F1 intercrosses of the CC (CC-RIX) allow for studies of replicable outbred mice. Researchers often seek to characterize and genetically dissect traits through heritability estimation and mapping regulatory genetic loci. Here we evaluate the relative merits of these populations for these tasks through simulation, as well as provide recommendations for performing the quantative analyses. We find that sample populations that include replicate animals, as possible with the CC and CC-RIX, provide more efficient and precise estimates of heritability. CC-RIX populations with replicates enable heritability to be decomposed into additive and non-additive components. All populations of approximately 200 animals were well-powered to detect large effect loci that explain ≥ 40% of the phenotypic variation, but only large sample populations of 500 DO mice were well-powered to detect smaller effect loci (≤10%) for highly polygenic traits. All results were produced with our R package musppr, which we developed to simulate data and evaluate genetic analyses from user-provided genotypes from these MPPs.